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公开(公告)号:US10728773B2
公开(公告)日:2020-07-28
申请号:US15880848
申请日:2018-01-26
Applicant: Verizon Patent and Licensing Inc.
Inventor: Ye Ouyang , Le Su , Krishna Pichumani Iyer , Christopher M. Schmidt
Abstract: A Self-Organizing Network (SON) collects data pertaining to a first number of cells of a wireless network. The SON splits the collected data into a second number of groups, and, for each of the second number of groups, repeatedly set a third number of clusters to a different number between a low limit and a high limit. The SON, for each of the settings, clusters the cells into the third number of clusters and trains a deep neural network to perform a regression analysis on the third number of clusters. For each of the second number of groups, the SON also determines an optimum number of clusters based on the regression analyses, re-clusters the cells into the optimum number of clusters; and tunes engineering parameters based on the re-clustering to optimize performance of the wireless network and quality of experience pertaining to the wireless network.
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公开(公告)号:US10667155B2
公开(公告)日:2020-05-26
申请号:US16036253
申请日:2018-07-16
Applicant: Verizon Patent and Licensing Inc.
Inventor: Ye Ouyang , Krishna Pichumani Iyer , Zhenyi Lin , Le Su
Abstract: A method, a device, and a non-transitory storage medium for estimating voice call quality include performing automatic speech recognition, for each of a plurality of voice calls, to generate recognized text for both an originating device acoustic signal and a receiving device acoustic signal. The recognized text for both the originating device acoustic signal and the receiving device acoustic signal are compared to the reference text to identified recognition errors and a voice call quality score for each of the originating device acoustic signal and the receiving device acoustic signal are determined. A correlation between the network conditions and the voice call quality scores is then determined.
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公开(公告)号:US10548032B2
公开(公告)日:2020-01-28
申请号:US15880855
申请日:2018-01-26
Applicant: Verizon Patent and Licensing Inc.
Inventor: Ye Ouyang , Le Su , Krishna Pichumani Iyer , Christopher M. Schmidt , Wenyuan Lu , Shaun Robert Pola , Maulik Shah
Abstract: A system may collect, from a wireless network, first data pertaining to nodes in the wireless network. Each datum of the first data belongs to one of two or more categories/For each of the nodes, for each of the categories, and for each datum belonging to the category, the system may determine if the datum is outside of a first range of values, and if the datum is inside the first range, the system may calculate a first base network performance health (NPH) score that is a function of the nodes, the categories, the data, and time. The system may also apply first deep learning to a first neural network among a plurality of neural networks to update first coefficients for correlating the first base NPH score to a mean opinion score, for each of the categories.
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公开(公告)号:US20200022007A1
公开(公告)日:2020-01-16
申请号:US16036253
申请日:2018-07-16
Applicant: Verizon Patent and Licensing Inc.
Inventor: Ye Ouyang , Krishna Pichumani Iyer , Zhenyi Lin , Le Su
Abstract: A method, a device, and a non-transitory storage medium for estimating voice call quality include performing automatic speech recognition, for each of a plurality of voice calls, to generate recognized text for both an originating device acoustic signal and a receiving device acoustic signal. The recognized text for both the originating device acoustic signal and the receiving device acoustic signal are compared to the reference text to identified recognition errors and a voice call quality score for each of the originating device acoustic signal and the receiving device acoustic signal are determined. A correlation between the network conditions and the voice call quality scores is then determined.
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公开(公告)号:US20190239095A1
公开(公告)日:2019-08-01
申请号:US15880848
申请日:2018-01-26
Applicant: Verizon Patent and Licensing Inc.
Inventor: Ye Ouyang , Le Su , Krishna Pichumani Iyer , Christopher M. Schmidt
Abstract: A Self-Organizing Network (SON) collects data pertaining to a first number of cells of a wireless network. The SON splits the collected data into a second number of groups, and, for each of the second number of groups, repeatedly set a third number of clusters to a different number between a low limit and a high limit. The SON, for each of the settings, clusters the cells into the third number of clusters and trains a deep neural network to perform a regression analysis on the third number of clusters. For each of the second number of groups, the SON also determines an optimum number of clusters based on the regression analyses, re-clusters the cells into the optimum number of clusters; and tunes engineering parameters based on the re-clustering to optimize performance of the wireless network and quality of experience pertaining to the wireless network.
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公开(公告)号:US10334463B2
公开(公告)日:2019-06-25
申请号:US15497326
申请日:2017-04-26
Applicant: Verizon Patent and Licensing Inc.
Inventor: Kyriaki Konstantinou , Ye Ouyang
Abstract: A device may receive information that identifies a first set of parameter values associated with a first set of access points. The first set of access points may be associated with a set of known access point quality scores. The device may generate a model based on the set of known access point quality scores and the first set of parameter values. The device may receive information that identifies a second set of parameter values associated with a second set of access points. The device may determine a set of access point quality scores, for the second set of access points, based on the second set of parameter values and the model. The device may provide information to permit an action to be performed in association with the second set of access points.
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公开(公告)号:US20190036795A1
公开(公告)日:2019-01-31
申请号:US15661224
申请日:2017-07-27
Applicant: Verizon Patent and Licensing Inc.
Inventor: Ye Ouyang , Krishna Pichumani Iyer , Christopher M. Schmidt , Jogendra Yaramchitti
Abstract: A method, a device, and a non-transitory storage medium provide for an anomaly detection and remedial service that includes receiving data from a network; performing a Gaussian Probabilistic Latent Semantic Analysis (GPLSA) using the data; detecting anomaly data included in the data based on the GPLSA; and invoking a remedial measure in the network based on the detection. The anomaly detection and remedial service may detect known and unknown anomalies. Additionally, the anomaly detection and remedial service may proactively and reactively detect anomalies.
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公开(公告)号:US20180262433A1
公开(公告)日:2018-09-13
申请号:US15974837
申请日:2018-05-09
Applicant: Verizon Patent and Licensing Inc.
Inventor: Ye Ouyang , Carol Becht , Krishna Pichumani Iyer , Le Su
CPC classification number: H04L47/2416 , H04L41/5035 , H04L43/08 , H04L43/0829 , H04L43/0847 , H04L43/087 , H04L43/0888 , H04L65/608 , H04L65/80 , H04M3/2236 , H04M7/006 , H04M2207/185 , H04W24/08 , H04W84/12
Abstract: A method, a device, and a non-transitory storage medium provide receiving a plurality of voice call quality values and values for a plurality key performance indicators (KPIs) related to voice over Wi-Fi voice call quality; selecting a subset of the plurality of KPIs based on a correlation between each KPI and the voice call quality value; performing a plurality of discrete regression analyses based on the subsets of the plurality of KPIs and the voice call quality values to generate a plurality of regression results; determining an accuracy for each of the plurality of regression results; assigning weights to each of the plurality of regression results based on the determined accuracies; and combining the plurality of regression results using the assigned weights to generate a final combined estimated VoWiFi voice call quality algorithm that accurately predicts the voice call quality value based on values for the selected subset of the plurality of KPIs.
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公开(公告)号:US20180227930A1
公开(公告)日:2018-08-09
申请号:US15941552
申请日:2018-03-30
Applicant: Verizon Patent and Licensing Inc.
Inventor: Ye Ouyang , Carol Becht , Krishna Pichumani Iyer
CPC classification number: H04W72/085 , H04L41/0896 , H04L41/16 , H04L41/5009 , H04W16/00 , H04W24/08
Abstract: A recursive algorithm may be applied to group cells in a service network into a small number of clusters. For each of the clusters, different regression algorithms may be evaluated, and a regression algorithm generating a smallest error is selected. A total error for the clusters may be identified based on the errors from the selected regression algorithms and from degrees of separation associated with the cluster. If the total error is greater than a threshold value, the cells may be grouped into a larger number of clusters and the new clusters may be re-evaluated. A key performance indicator (KPI) may be estimated for a cell based on a regression algorithm selected for the cluster associated with the cell. A resources may be allocated to the cell based on the KPI value.
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公开(公告)号:US09992123B2
公开(公告)日:2018-06-05
申请号:US15199265
申请日:2016-06-30
Applicant: Verizon Patent and Licensing Inc.
Inventor: Ye Ouyang , Carol Becht , Krishna Pichumani Iyer , Le Su
CPC classification number: H04L47/2416 , H04L41/5035 , H04L43/08 , H04L43/0829 , H04L43/0847 , H04L43/087 , H04L43/0888 , H04L65/608 , H04L65/80 , H04M3/2236 , H04M7/006 , H04M2207/185 , H04W24/08 , H04W84/12
Abstract: A method, a device, and a non-transitory storage medium provide receiving a plurality of voice call quality values and values for a plurality key performance indicators (KPIs) related to voice over Wi-Fi voice call quality; selecting a subset of the plurality of KPIs based on a correlation between each KPI and the voice call quality value; performing a plurality of discrete regression analyses based on the subsets of the plurality of KPIs and the voice call quality values to generate a plurality of regression results; determining an accuracy for each of the plurality of regression results; assigning weights to each of the plurality of regression results based on the determined accuracies; and combining the plurality of regression results using the assigned weights to generate a final combined estimated VoWiFi voice call quality algorithm that accurately predicts the voice call quality value based on values for the selected subset of the plurality of KPIs.
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